MIRAGE-Base
This repo contains the the official weights of the MIRAGE-Base model (based on ViT-Base), from the paper "MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysis", by José Morano et al. (2025).
Project page: MIRAGE.
MIRAGE models
Usage
The model can be loaded using the PyTorchModelHubMixin
from the huggingface_hub
package and the code from the mirage_hf.py
script that can be downloaded from here.
from huggingface_hub import PyTorchModelHubMixin
from mirage_hf import MIRAGEWrapper
class MIRAGEhf(MIRAGEWrapper, PyTorchModelHubMixin):
def __init__(
self,
input_size=512,
patch_size=32,
modalities='bscan-slo',
size='base',
):
super().__init__(
input_size=input_size,
patch_size=patch_size,
modalities=modalities,
size=size,
)
# For the MIRAGE model based on ViT-Base
model = MIRAGEhf.from_pretrained("j-morano/MIRAGE-Base")
# For the MIRAGE model based on ViT-Large
model = MIRAGEhf.from_pretrained("j-morano/MIRAGE-Large")
Citation
If you use our code or our model in your research, we would greatly appreciate it if you give a star to the repo and cite our work:
@misc{morano2025mirage,
title={{MIRAGE}: Multimodal foundation model and benchmark for comprehensive retinal {OCT} image analysis},
author={José Morano and Botond Fazekas and Emese Sükei and Ronald Fecso and Taha Emre and Markus Gumpinger and Georg Faustmann and Marzieh Oghbaie and Ursula Schmidt-Erfurth and Hrvoje Bogunović},
year={2025},
eprint={2506.08900},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2506.08900},
}
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